kevinwu2981

Definitely. Do you want to leave behind your contact info on our website and I will reach out to you?

It seems you tried the English demo. Wondering was the website in English or German for you?

We see the main value prop of voice AI to be to enable higher volumes of calls in a cost-efficient manner. It is clear that there is a slight trade-off on quality, because humans will do a better job in "high-stakes" calls and where creativity is more required.

It thus makes sense why it might not work for legal, since every call there might be high stakes.

Having the bot be "creative" is actually an interesting proposition. We currently do not focus on it, since the majority of our customers want the bot to be predictable and not hallucinate.

The German call center market is very large, established and well-organised. Also pricing power here is often higher, because you cannot outsource call center work to outside Germany (because no one speaks German).

We are using Vercel

This is on the roadmap. We haven’t yet been able to execute on this, since we are still laying the foundations, but this is a great idea!!

Interesting and seems like a great use case. We currently focus on working with businesses though:/

Essentially you are currently optimizing for the majority. Looking forward to how that develops over time as conversations get more personalized

Also every stakeholder might value different things: call deflection rate, CSAT, number of bookings, etc. Important to align expectations upfront

It is very scalable. We currently handle >100k calls per day on our platform.

Why do you think it didn't work out in legal? We currently don't focus on that domain.

In general, we currently have really high success rates with relatively constrained use cases, such as lead qualification and well scoped customer service use cases (e.g., appointment booking, travel cancellation).

In general, voice AI is hard because WYSIWYG (there is no human in the loop between what the bot is saying and what the person on the other side gets to hear). Not sure about legal, but for more complex use cases (e.g., product refunds in retail), there are many permutations in how two different customers might frame the same issue and so it might be harder to accurately instruct the AI agent in a way to guarantee high automation results (given plentitude of edge cases).

It is our belief therefore that voice AI works the best, when the bot is leading the conversation and it is always very clear what the next steps are...

I got the demo request:) Let me reply to you

Comparable in some aspects. Their focus is dev-tooling, while we are a mid-market and enterprise solution, geared towards enabling non-technical users at those companies, by using our tools, to easily create voice AI agents for customer service, lead qualification and ops use cases

Livekit started as an infra for real-time audio/video applications. We are actually using them for WebRTC. They recently started growing into the voice AI space, but are still more of an infra solution, while we are an end-to-end platform.

What sets us apart is multi-stage conversation modeling, out-of-the-box evals, and self-improvement!

Thanks! We provide eval templates that can be applied on specific stages or the whole conversation. Users can specify their own evals that can be as granular as they'd like. We're also working on conversation simulation feature that lets users quickly iterate on evals via simulating previous real conversations and seeing if the eval output aligns with human judgement.

P.S. Arkadiy is locked out of his HN account due to the anti-procrastination settings. HN team, can you plz help? :)